Abstract 4547: High dimensional proteomic profiling of immune cell subsets with data-independent acquisition mass spectrometry
Authors: Jakob Vowinckel, Tobias Treiber, Kristina Beeler, Nicholas Dupuis
Journal: Cancer Research (2019)

Abstract Background Recent success with therapies to activate the immune system has demonstrated the utility of targeting the immune system for control of multiple cancers. These successes have also spurred interest in characterizing immune cell sub-populations to understand mechanisms of activation and suppression, and their relationship to therapeutic response. Currently, antibody-based approaches are commonly used to characterize immune cells, however these methods are limited to 30-40 markers and are driven by previous hypotheses, limiting new discovery. In this context, determination of the surface and cellular proteome of responsive populations will provide a powerful tool for insight into response mechanisms, so far hampered by low sample material availability and insufficient sensitivity of proteomic methodology. Here, we demonstrate how data-independent acquisition mass spectrometry can be used for high-dimensional characterization of immune cells, even with very limited cell numbers. Methods Primary human Cytotoxic CD8+ T cells, CD4+ T cells, CD14+ monocytes and natural killer (NK) cells, isolated from peripheral blood mononuclear cells, were prepared for mass spectrometry using standard sample preparation workflows. All samples were analyzed using 2 and 4 hour LC gradients on a C18 column coupled to a Thermo Scientific Q Exactive HF mass spectrometer in data-independent acquisition (DIA-MS) mode. DIA data was extracted using Spectronaut Pulsar X (Biognosys) both with a library generated using directDIA data searching in Spectromine as well as a Hybrid Library combining the directDIA and a publicly available resource library. Results Cytotoxic CD8+ T cells were evaluated using 100,000 cells of input material, which resulted in more than 3,500 proteins quantified in the primary cells. When combined with a CD8+ T cell resource library, the number of proteins quantified was more than 5,000. In the current experimental setup, 30,000 cells defines the lower limit of detection of CD8A and CD8B. Among other previously characterized proteins associated with CD8+ T cells, CCL5, TBX21, GZMH, PRF1, GNLY, CST7 were all detected at 30,000 cell input. Additionally, Granzyme A and B were also quantified which have classically been used, along with PRF1, as markers of lymphocyte infiltration. Data will also be presented for CD4+ T cells, CD14+ monocytes, and NK cells to further map and compare the immune cell phenotypic landscapes. Conclusions The DIA-MS platform enables deep proteomic phenotyping of sorted immune cell samples, even with limited numbers of cells. These new data sets make available broad and un-constrained biomarker investigation for deconvolution of the processes driving immune cell activation and suppression. Citation Format: Jakob Vowinckel, Tobias Treiber, Kristina Beeler, Nicholas Dupuis. High dimensional proteomic profiling of immune cell subsets with data-independent acquisition mass spectrometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4547.